Deconvolution of Images from BLAST 2005: Insight into the K3-50 and IC 5146 Star-Forming Regions
Arabindo Roy, Peter A. R. Ade, James J. Bock, Christopher M. Brunt,, Edward L. Chapin, Mark J. Devlin, Simon R. Dicker, Kevin France, Andrew G., Gibb, Matthew Griffin, Joshua O. Gundersen, Mark Halpern, Peter C. Hargrave,, David H. Hughes, Jeff Klein, Gaelen Marsden

TL;DR
This paper demonstrates an improved image deconvolution method for submillimeter telescope data, applying it to star-forming regions K3-50 and IC 5146, revealing detailed structures and physical properties of clumps and protostars.
Contribution
The paper introduces an implementation of the Lucy-Richardson deconvolution for BLAST data and applies it to reveal new insights into star-forming regions, improving image resolution and analysis.
Findings
Resolved three clumps in K3-50 with detailed physical properties.
Identified ten compact sources with cold temperatures and associated YSOs.
Restored large-scale structures in IC 5146 correlating with other observations.
Abstract
We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available highresolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the Spectral Energy Distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T).…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
